Thesis (Ph. D. in Electrical Engineering)--Vanderbilt University, Aug. 2006. / Title from title screen. Includes bibliographical references.

Not available / text

As the container traffic at the Port of Savannah is expected to increase, its impacts need to be evaluated to address major concerns regarding the roadway network surrounding the port and the overall operations of the port. A federation of two disparate simulators was created in order to model the impacts of increased container traffic. The Port of Savannah was modeled using Rockwell Arena© and the surrounding roadway network was modeled using PTV VISSIM©. These two simulators operated concurrently and continually provided feedback with one another. The challenges that arose from this combination were largely due to the time structure of the models. Arena© is a discrete event simulator and VISSIM© is a continuous traffic simulator. A basic model, where these two pieces of software could pass information between one another, was initially created as a test bed for methods required to federate the two models. These basic concepts were then applied to a comprehensive model of the Port of Savannah and the surrounding area. This federated modeling approach for the Port of Savannah allowed the analysis to reflect the interaction of behaviors unique to the port and local roadway network. For instance, the federated model successfully captured how delays at the Port of Savannah increased as a result of increased congestion in the surrounding roadway network. It is anticipated that this prototypal model will be a base for future research into the area of federating disparate transportation simulators, as well as aid in the further exploration of a transportation run-time interface.

Thesis (M. S. in Computer Science)--Vanderbilt University, May 2005. / Title from title screen. Includes bibliographical references.

Thesis (M. S.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Hunter, Michael; Committee Member: Laval, Jorge; Committee Member: Rodgers, Michael. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

Distributed computing systems (DCS) host a wide variety of enterprise applications in dynamic and uncertain operating environments. These applications require stringent reliability, availability, and quality of service (QoS) guarantee to maintain their service level agreements (SLAs). Due to the growing size and complexity of DCS, an autonomic performance management system is required to maintain SLAs of these applications. A model-based autonomic performance management structure is developed in this dissertation for applications hosted in DCS. A systematic application performance modeling approach is introduced in this dissertation to define the dependency relationships among the system parameters, which impact the application performance. The developed application performance model is used by a model-based predictive controller for managing multi-dimensional QoS objectives of the application. A distributed control structure is also developed to provide scalability for performance management and to eliminate the requirement of approximate behavior modeling in the hierarchical arrangement of DCS. A distributed monitoring system is also introduced in this dissertation to keep track of computational resources utilization, application performance statistics, and scientific application execution in a DCS, with minimum latency and controllable resource overhead. The developed monitoring system is self-configuring, self-aware, and fault-tolerant. It can also be deployed for monitoring of DCS with heterogeneous computing systems. A configurable autonomic performance management system is developed using modelintegrated computing methodologies, which allow administrators to define the initial settings of the application, QoS objectives, system components’ placement, and interaction among these components in a graphical domain specific modeling environment. This configurable performance management system facilitates reusability of the same components, algorithms, and application performance models in different deployment settings.

Model development decisions are an important feature of engineering design. The quality of simulation models often dictates the quality of design decisions, seeing as models guide decision makers (DM) in choosing design decisions. A quality model accurately represents the modeled system and is helpful for exploring what-if scenarios, optimizing design parameters, estimating design performance, and predicting the effect of design changes. However, obtaining a quality model comes at a cost in terms of model development--in experimentation, labor, model development time, and simulation time. Thus, DMs must make appropriate trade-offs when considering model development decisions. The primary challenge in model development is making decisions under significant uncertainty. This thesis addresses model development in the conceptual design phase where uncertainty levels are high. In the conceptual design phase, there are many information constraints which may include an incomplete requirements list, unclear design goals, and/or undefined resource constrains. During the embodiment design phase, the overall objective of the design is more clearly defined, and model development decisions can be made with respect to an overall objective function. For example, the objective may be to maximize profit, where the profit is a known function of the model output. In the conceptual design phase, this level of clarity is not always present, so the DM must make decisions under significant model uncertainty and objective uncertainty. In this thesis, conjoint analysis is employed to solicit the preferences of the decision maker for various model attributes, and the preferences are used to formulate a quasi-objective function during the conceptual design phase--where the overall design goals are vague. Epistemic uncertainty (i.e., imprecision) in model attributes is represented as intervals and propagated through the proposed model development framework. The model development framework is used to evaluate the best course of action (i.e., model development decision) for a real-world packaging design problem. The optimization of medical product packaging is assessed via mass spring damper models which predict contact forces experienced during shipping and handling. Novel testing techniques are employed to gather information from drop tests, and preliminary models are developed based on limited information. Imprecision in preliminary test results are quantified, and multiple model options are considered. Ultimately, this thesis presents a model development framework in which decision makers have systematic guidance for choosing optimal model development decisions.